similar to: Problem with NAs using chisq.test() (PR#748)

Full_Name: Kjetil Kjernsmo Version: 1.0.1 OS: osf1 Submission from: (NULL) (129.240.28.227) Ouch, another obscure bug... I just had a bus error crash, with a core dump, a small one this time. Usual <URL:http://www.astro.uio.no/~kjetikj/tmp/core>. I had done a few simulations, and done a chisq.test() on them. These simulations also write about 190MB's to file, but I have no idea whether

On 8 Nov 2000, Peter Dalgaard BSA wrote: >Done... Great! >(This kind of behaviour has been observed on various platforms and >various compilers, sometimes getting stuck around 15.15 and sometimes >around 14.5. Others report no problems. Very strange. I've seen one >case where it apparently shifted from one regime to the other.) Yes, it does that here too.... The following is

This is a message for whoever maintains "chisq.test": For an outcome more extreme than 2000 simulations, a Monte Carlo p-value of "< 2.2e-16" was printed. Ripley said the proper p-value for such cases should be 1/(B+1) = 1/2001. This can be easily fixed by adding "if(PVAL==0)PVAL <- 1/(B+1)" right after the following line in the code for chisq.test (in R

If you wanted to do a t.test res1<-do.call(cbind,lapply(seq_len(nrow(m)),function(i) do.call(rbind,lapply(split(rbind(m[i,-1],n),1:nrow(rbind(m[i,-1],n))), function(x) {x1<- rbind(x,m[i,-1]); t.test(x1[1,],x1[2,])$p.value})))) ?res2<-do.call(cbind,lapply(seq_len(ncol(res1)),function(i) c(c(tail(res1[seq(1,i,1),i],-1),1),res1[-c(1:i),i]))) ?attr(res2,"dimnames")<-NULL ?res2

Full_Name: Kjetil Kjernsmo Version: 1.0.0 OS: osf1 Submission from: (NULL) (129.240.28.227) Hello! I'm afraid I have another obscure bug. R has just crashed with a segmentation fault. This time, I have even failed to reproduce it, but fortunately, I have a core dump. It's at <URL:http://www.astro.uio.no/~kjetikj/tmp/core> The call I did was log10(quantile(chisqtests5M11001,

I am getting "Chi-squared approximation may be incorrect in: chisq.test(x)" with the data bleow. Frequency distribution of number of male offspring in families of size 5. Number of Male Offspring N 0 518 1 2245 2 4621 3 4753 4 2476 5

Dear all, I think I must be going crazy.... If I do > mean(rpois(1000000, 14)) I get: [1] 13.50420 and again: > mean(rpois(1000000, 14)) [1] 13.49896 > mean(rpois(1000000, 14)) [1] 13.50161 > mean(rpois(1000000, 15)) [1] 14.49250 > mean(rpois(1000000, 15)) [1] 14.49897 > mean(rpois(1000000, 14.5)) [1] 13.99689 > mean(rpois(1000000, 14.5)) [1] 13.9963 This was on a platform

Dear all, I have some difficulty getting R-1.3.0 to run on the alpha, with osf4.0e (Tru64, or whatever they call it... :-) ). configure reports the following configuration: R is now configured for alphaev6-dec-osf4.0e Source directory: . Installation directory: /astro/local C compiler: gcc -mieee -g -O2 C++ compiler: c++ -g -O2 FORTRAN

Dear all, I have some difficulty getting R-1.3.0 to run on the alpha, with osf4.0e (Tru64, or whatever they call it... :-) ). configure reports the following configuration: R is now configured for alphaev6-dec-osf4.0e Source directory: . Installation directory: /astro/local C compiler: gcc -mieee -g -O2 C++ compiler: c++ -g -O2 FORTRAN

Dear all, I'm making a system to create a star-chart, and I have encountered one of the intuitive and clearly thoughtful conventions that are so common in astronomy :-J... Well, the point being, I have to reverse the x-axis. I figured, I might just set xlim=rev(range(x)). Do e.g. > x <- 0:5 > y <- (0:5)^3 > plot(x, y) > plot(x, y, xlim=rev(range(x))) The problem is that here

chisq.test with simulate.p.value=TRUE uses the Patefield algorithm, this is not documented, and the original reference is not given, as it ought to be. The reference is: Patefield,W. M. (1981) An efficient method of generating r * c tables with given row and column totals (algorithm AS 159). Applied Statistics 30, 91-97. Kjetil Halvorsen

Hi, I have a text mining project and currently I am working on feature generation/selection part. My plan is selecting a set of words or word combinations which have better discriminant capability than other words in telling the group id's (2 classes in this case) for a dataset which has 2,000,000 documents. One approach is using "contrast-set association rule mining" while the

The cells are interpreted as counts, so by scaling you're analyzing a different experiment (one with fewer observations). So the chi-squared value will change (the terms (O-E)^2/E in the statistic scale linearly ignoring rounding and "Yates' continuity correction"). The chisq.test on the original data is a test of association. Conventionally you decide ahead of time on a

Question for 'experts' in LP using R (using the lpSolve package, say) -- which does not apply to me for the sort of problem I describe below. I've run any number of LP's using lpSolve in R, but all of them to date have objective and constraint functions that both contain the same variables. This lets you set up a LHS and RHS matrix/vector that are symmetrical. But, for a

Apart from the fact that the statement "such that t1+t2+t3+t4=2970 (as it must)" is not correct, the LP can be implemented as follows: library(lpSolve) LHS <- rbind( c(0,0,0,0, 1, 0, 0,0), c(1,0,0,0,-1, 1, 0,0), c(0,1,0,0, 0,-1, 1,0), c(0,0,1,0, 0, 0,-1,1), cbind(-diag(4),diag(4)), c(0,0,0,0,0,1,0,0), c(0,0,0,0,0,0,1,0), c(0,0,0,0,0,0,0,1) ) RHS <-

Hi, In the chisq.test(), if the expected frequency for some categories is <5, there will be a warning message which says Warning message: Chi-squared approximation may be incorrect in: chisq.test(x, p = probs) I am wondering whether there are some methods to get rid of this mistake... Seems the ?chisq.test() doesn''t provide more options to solve this problem. Or, the only choice is

Dear all, I have a question about the chisq.test command. As an option one can chose the computation of p-values by Monte-Carlo simulation (simulate.p.value=T). Is there any documentation available how this calculations are done and how this simulation based test behaves in small samples? Thanks Klaus Abberger University of Konstanz, Germany [[alternate HTML version deleted]]

Hi all, I am new to python, R and rpy2. I having few errors when I am using 'fisher.test' function where I am struck now. Please help to fix these bugs. My code for fisher.test goes this way *from rpy2 import * import rpy2.robjects as robjects def fisherExact(a,b,c,d): v = [a,b,c,d] m = robjects.r['matrix'](v,2,2) s = robjects.r['fisher.test'](m) return s *

Full_Name: Kjetil Kjernsmo Version: Version 1.0.0 OS: osf1 Submission from: (NULL) (129.240.28.227) Hello again! This is a follow-up to my message on R-help about a problem with match.arg() I have a little more on the topic, but not much really. First, it was not entirely true what I wrote in r-help that I call match.arg() in my ramp(), because ramp() just calls qamp() with runif() as

>>>>> "TL" == Thomas Lumley <thomas@biostat.washington.edu> writes: on Subject: Re: [Rd] Problem with NAs using chisq.test() (PR#748) which I've changed, since it is another bug we are talking about now TL> On Sun, 26 Nov 2000 kjetikj@astro.uio.no wrote: >> Full_Name: Kjetil Kjernsmo .............. .............. TL> However,